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The University of Maryland researchers who first explored ideas at the core of Google’s AlphaGo have written an article for the October issue of OR/MS Today, the main magazine of the professional society INFORMS (Institute for Operations Research and the Management Sciences). AlphaGo is the artificial intelligence (AI) system that defeated Go master Lee Se-Dol in early March. (Read our original story here.)

The article, “Google DeepMind’s AlphaGo,” was co-written by former Institute for Systems Research (ISR) Postdoctoral Researcher Hyeong Soo Chang, now a professor at Sogang University in Korea; Professor Michael C. Fu (Smith School/ISR); Jiaqiao Hu, (ECE Ph.D. 2006), now an associate professor at Stony Brook University; and Professor Steven I. Marcus (ECE/ISR). They originally collaborated on the paper, “An adaptive sampling algorithm for solving Markov decision processes,” which was a seminal influence on AlphaGo. It appeared in the January-February 2005 issue of the journal Operations Research.

In the article, the authors talk about how their ideas influenced the development of AlphaGo. They also delve into disconnects between the operations research (OR) and computer science/artificial intelligence (CS/AI) communities that hinder idea sharing between the disciplines. They argue that disciplines’ very different academic cultures make things difficult—for example, while the CS/AI community mainly publishes through conference proceedings, the OR community values journal publications. The authors then suggest ways these communities could interact in a mutually beneficial way to build on the research strengths of both.

| Read the article here |



Related Articles:
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AlphaGo family of AI programs grew from AMS simulation-based algorithms developed at UMD
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A new unbiased stochastic derivative estimator for simulating complex systems
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Michael Fu wins NSF grant for simulation-based optimal decision making

November 8, 2016


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